This chapter focusses on the development of a new image processing technique for the processing of large and complex images, especially SAR images. We propose here a new and effective approach that outperforms the existing methods for the calculation of high order textural parameters. With a single processor, this approach is about times faster than the co-occurrence matrix approach considered as classical, where is the order of the textural parameter for a 256-gray scales image. In a parallel environment made of N processor, this performance can almost be multiply by the factor N. Our approach is based on a new modeling of textural parameters of a generic order 1$$]] equivalent to the classical formulation, but which is no longer based on the co-occurrence matrix of order 1$$]]. By avoiding the calculation of the co-occurrence matrix of order 1$$]], the resulted model enables a gain of about bytes of the required memory space.
CITATION STYLE
Talla Tankam, N., Dipanda, A., Bobda, C., Fotsing, J., & Tonyé, E. (2014). A parallel approach for statistical texture parameter calculation. In Distributed Embedded Smart Cameras: Architectures, Design and Applications (Vol. 9781461477051, pp. 231–255). Springer New York. https://doi.org/10.1007/978-1-4614-7705-1_11
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